A Generic Battery Model and Its Parameter Identification

Datong Song, Colin Sun, Qianpu Wang, Darren Jang
2018 Energy and Power Engineering  
A new dynamic model is developed in this paper based on the generic MATLAB battery model. The battery capacity is expressed as a function of the self-discharge rate, the discharge current, the cycling life and the temperature of the battery. The dependence of the model parameters on cycle life and temperature are estimated from the first order approximation. The detailed procedures and formula to extract the model parameters are presented and the extraction relies only on the discharge curves
more » ... discharge curves at two different discharge currents, at two different life cycles, and at two different temperatures. These discharge curves are typically provided in the battery manufacturer's datasheet. The proposed model is verified for both nickel-metal hydride and lithium-ion batteries by comparing the calculated discharge curves with the results from the generic MATLAB model. The model is further validated for the Sinopoly lithium-ion battery (SP-LFP1000AHA) by comparing the model results with the discharge curves from the manufacturer's datasheet at different discharge currents, different cycling numbers, and different temperatures. Simulation results show that the new model can correctly predict voltage separation beyond the nominal zone while maintaining the same level of accuracy as the generic MATLAB model in the exponential and nominal zones. Energy and Power Engineering generation, transmission, and distribution of electric energy, especially in the case of the high penetration of intermittent renewable energy from wind and solar power generation [1] . When an ESS relies on an electrochemical storage technology like batteries, an accurate model of its voltage and capacity is essential to evaluating the system's ability to perform various function required for grid applications. The ESS controller must rely on this model in order to safely and reliably operate the ESS. The existing mathematical battery models vary widely in terms of chemistries, reactions, and geometries modelled. In general, as more detailed physiochemical phenomena are included in a battery model, its simulation results can be expected to be more reliable, but at the cost of increased computational effort. Therefore, an accurate yet relatively simple dynamic mathematical model is required for the battery management systems (BMS) to facilitate efficient ESS control in grid applications so that the charging/discharging processes can be properly managed to optimize battery performance and durability. According to their modeling methodology, battery models can be classified as Electrochemical Multiphysics, Equivalent Circuit (EC), and Empirical or semiempirical dynamic models [2] . Electrochemical Multiphysics battery models [3] consider the fundamental battery chemistry and multiphase transport theory to study the effects of the reaction kinetics and geometry on battery performance. The Electrochemical Multiphysics models are well developed but are not suitable for grid applications due to their complicated coupling of species reaction and transport equations. The equivalent circuit battery models [4] employ the passive circuit elements like capacitors, inductors and resistors to model electrolyte, D. Song et al.
doi:10.4236/epe.2018.101002 fatcat:4wbfs5erxnbjhg6w4fa52qskqq